Discover @dog-qiuqiu Open Source projects

xuehao.ma (@dog-qiuqiu)

dog-qiuqiu

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Location 🇨🇳 China
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Yolo-Fastest

⚡ Based on yolo's ultra-lightweight universal target detection algorithm, the calculation amount is only 250mflops, the ncnn model size is only 666kb, the Raspberry Pi 3b can run up to 15fps+, and the mobile terminal can run up to 178fps+

MobileNet-Yolo

MobileNetV2-YoloV3-Nano: 0.5BFlops 3MB HUAWEI P40: 6ms/img, YoloFace-500k:0.1Bflops 420KB🔥🔥🔥

Yolo-FastestV2

⚡ Based on Yolo's low-power, ultra-lightweight universal target detection algorithm, the parameter is only 250k, and the speed of the smart phone mobile terminal can reach ~300fps+

FastestDet

⚡ A newly designed ultra lightweight anchor free target detection algorithm， weight only 250K parameters， reduces the time consumption by 10% compared with yolo-fastest, and the post-processing is simpler

Ultralight-SimplePose

Ultra-lightweight human body posture key point CNN model. ModelSize:2.3MB HUAWEI P40 NCNN benchmark: 6ms/img,

simple-rknn2

The rknn2 API uses the secondary encapsulation of the process, which is easy for everyone to call. It is applicable to rk356x rk3588

Android_NCNN_yolov4-tiny

yolov4-tiny ncnn android sample

Android_MobileNetV2-YOLOV3-Nano-NCNN

MobileNetV2-YOLOV3-Nano NCNN sample

libopencv

Opencv ARM Linux precompiled library

Simple-TensorRT

Secondary encapsulation of NVIDIA TensorRT interface to simplify the calling process

dog-qiuqiu